Ontology for E-Learning: A Bayesian Approach

In the last decade, the evolution of educational technologies has forced an extraordinary interest in new methods for delivering learning content to learners. Today, distance education represents an effective way for supporting and sometimes substituting the traditional formative processes, thanks to the technological improvements achieved in the field in recent years. However, the role of technology has often been overestimated. The amount of information students can obtain from the Internet is huge, and as a result, they can easily be confused. Teachers can also be disconcerted by this vast quantity of content and are often unable to suggest the correct content to their students. In the open scientific literature, it is widely recognized that an important factor for success in delivering learning content is related to the capability for customizing the learning process for the specific needs of a given learner. This task is still far from having been fully accomplished, and there is a real interest in investigating new approaches and tools to adapt the formative process to specific individual needs. In this scenario, the introduction of ontology formalism can improve the quality of the formative process, allowing the introduction of new and effective services. Ontologies can lead to important improvements in the definition of a course's knowledge domain, in the generation of an adapted learning path, and in the assessment phase. This paper provides an initial discussion of the role of ontologies in the context of e-learning. The improvements related to the introduction of ontologies formalism in the e-learning field are discussed, and a novel algorithm for ontology building through the use of Bayesian networks is shown. Finally, the application of this algorithm in the assessment process and some experimental results are illustrated.